Work

Decoding the complexity of tricuspid regurgitation prognostic drivers using explainable artificial intelligence

Year: 2026

Type: article

Study design: Observational Study

Source: European Heart Journal - Cardiovascular Imaging

DOI: 10.1093/ehjci/jeag168

Authors: Gal Tsaban, Giovanni Benfari, Benjamin A Essayagh, Eunjung Lee, Manuel A Montoya Hernandez, Prabin Thapa, Vuyisile T Nkomo, Sorin V Pislaru, Hector I Michelena, Maurice Enriquez-Sarano

Institutions: Mayo Clinic, University of Verona

Language: English

Topic: Cardiac Valve Diseases and Treatments

Subfield: Cardiology and Cardiovascular Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W7166319034

FWCI: 4.63

Cites: 47

Cited by: 1

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